Validation of a single-nucleotide polymorphism panel for parentage testing of farmed red deer

Parentage Analysis in Giant Grouper (Epinephelus lanceolatus) Using Microsatellite and SNP Markers from Genotyping-by-Sequencing Data

Pedigree information is necessary for the maintenance of diversity for wild and captive populations. Accurate pedigree is determined by molecular marker-based parentage analysis, which may be influenced by the polymorphism and number of markers, integrity of samples, relatedness of parents, or different analysis programs. Here, we described the first development of 208 single nucleotide polymorphisms (SNPs) and 11 microsatellites for giant grouper (Epinephelus lanceolatus) taking advantage of Genotyping-by-sequencing (GBS), and compared the power of SNPs and microsatellites for parentage and relatedness analysis, based on a mixed family composed of 4 candidate females, 4 candidate males and 289 offspring. CERVUS, PAPA and COLONY were used for mutually verification. We found that SNPs had a better potential for relatedness estimation, exclusion of non-parentage and individual identification than microsatellites, and > 98% accuracy of parentage assignment could be achieved by 100 polymorphic SNPs (MAF cut-off < 0.4) or 10 polymorphic microsatellites (mean H_o = 0.821, mean PIC = 0.651). This study provides a reference for the development of molecular markers for parentage analysis taking advantage of next-generation sequencing, and contributes to the molecular breeding, fishery management and population conservation.

The future of parentage analysis: From microsatellites to SNPs and beyond

Parentage analysis is a cornerstone of molecular ecology that has delivered fundamental insights into behaviour, ecology and evolution. Microsatellite markers have long been the king of parentage, their hypervariable nature conferring sufficient power to correctly assign offspring to parents. However, microsatellite markers have seen a sharp decline in use with the rise of next-generation sequencing technologies, especially in the study of population genetics and local adaptation. The time is ripe to review the current state of parentage analysis and see how it stands to be affected by the emergence of next-generation sequencing approaches. We find that single nucleotide polymorphisms (SNPs), the typical next-generation sequencing marker, remain underutilized in parentage analysis but are gaining momentum, with 58 SNP-based parentage analyses published thus far. Many of these papers, particularly the earlier ones, compare the power of SNPs and microsatellites in a parentage context. In virtually every case, SNPs are at least as powerful as microsatellite markers. As few as 100-500 SNPs are sufficient to resolve parentage completely in most situations. We also provide an overview of the analytical programs that are commonly used and compatible with SNP data. As the next-generation parentage enterprise grows, a reliance on likelihood and Bayesian approaches, as opposed to strict exclusion, will become increasingly important. We discuss some of the caveats surrounding the use of next-generation sequencing data for parentage analysis and conclude that the future is bright for this important realm of molecular ecology.

How many markers are enough? Factors influencing parentage testing in different livestock populations

Reliability of parentage test panels is usually based on its power to exclude wrong parentage assignments based on allele frequencies. We evaluated the rates of false exclusions and inclusions in parentage assignments, and how these results are affected by allele frequencies, panel sizes and the number of allowed mismatches. We also evaluated the reliability of parentage testing by comparing populations with distinct genetic backgrounds using pure and composite families of cattle and sheep. Allowing for 1% genotype mismatches in true parent-offspring relations provided the best compromise between false-positive and false-negative assignments. Pure breeds needed at least 200-210 single-nucleotide polymorphism (SNP) markers to correctly assign relations, but between 700 and 890 markers to avoid assigning incorrect relationships. Composite breeds needed between 220 (sheep) and 500 (cattle) markers for correct assignment; 680 (cattle) to 4400 (sheep) SNPs were needed to eliminate false-positive assignments. Allowing 0% genotype mismatches decreased false-positive but increased false-negative assignments, whilst a higher threshold of 2% showed the opposite effects. Panels with high minor allele frequencies (0.35-0.45) provided the best chance for correct parentage resolutions requiring fewer markers. Further, we propose that a dynamic threshold would allow adapting to population specific error rates. A comparison to the performance of the official International Society for Animal Genetics SNP panel for cattle and a recently published SNP panel for sheep showed that randomly selected markers performed only slightly worse for the applied parentage test based on opposing homozygotes. This suggests that even with carefully selected panels, only marginal assignment improvements are obtainable for a particular number of SNPs. The main point for improvement is the number of markers used. We recommend using at least 200 SNP markers for parentage testing if the aim is to reduce false-negative results. To fully exclude false positives at least 700 markers are required.

A high throughput single nucleotide polymorphism multiplex assay for parentage assignment in New Zealand sheep

Accurate pedigree information is critical to animal breeding systems to ensure the highest rate of genetic gain and management of inbreeding. The abundance of available genomic data, together with development of high throughput genotyping platforms, means that single nucleotide polymorphisms (SNPs) are now the DNA marker of choice for genomic selection studies. Furthermore the superior qualities of SNPs compared to microsatellite markers allows for standardization between laboratories; a property that is crucial for developing an international set of markers for traceability studies. The objective of this study was to develop a high throughput SNP assay for use in the New Zealand sheep industry that gives accurate pedigree assignment and will allow a reduction in breeder input over lambing. This required two phases of development- firstly, a method of extracting quality DNA from ear-punch tissue performed in a high throughput cost efficient manner and secondly a SNP assay that has the ability to assign paternity to progeny resulting from mob mating. A likelihood based approach to infer paternity was used where sires with the highest LOD score (log of the ratio of the likelihood given parentage to likelihood given non-parentage) are assigned. An 84 “parentage SNP panel” was developed that assigned, on average, 99% of progeny to a sire in a problem where there were 3,000 progeny from 120 mob mated sires that included numerous half sib sires. In only 6% of those cases was there another sire with at least a 0.02 probability of paternity. Furthermore dam information (either recorded, or by genotyping possible dams) was absent, highlighting the SNP test’s suitability for paternity testing. Utilization of this parentage SNP assay will allow implementation of progeny testing into large commercial farms where the improved accuracy of sire assignment and genetic evaluations will increase genetic gain in the sheep industry.